Quickstart
Get started with Mixedbread's API. This guide introduces Embeddings and Reranking, essential tools for building smarter AI systems with improved accuracy and relevance.
We're drowning in data. With the explosion of content on the internet and within organizations, finding the right information at the right time has become a massive challenge. That's where search comes in.
Modern AI systems, especially large language models (LLMs), rely heavily on efficient search and retrieval to access relevant information. This is crucial for several reasons:
- Enhancing accuracy and relevance of AI-generated content
- Powering knowledge-intensive tasks like question answering and fact-checking
- Enabling retrieval-augmented generation (RAG) for more contextual and up-to-date responses
- Reducing hallucination in AI-generated content
In short, better search = smarter AI. And that's exactly what Mixedbread is here to help you build.
Jump right in
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Overview
Welcome to Mixedbread's documentation. Explore our state-of-the-art models and tools for smarter search and retrieval systems. Get started with our APIs, learn about embeddings and reranking, and join our community.
Embeddings
Quickly learn how to use Mixedbread's Embeddings API to generate vector representations of text. This guide provides a introduction to creating and utilizing embeddings for semantic search and other NLP tasks, with code examples to get you started immediately.